This invention relates to motion analysis systems and, more particularly, to an apparatus for analyzing a body having an illuminated marker placed thereon.
Analysis of the biomechanics of human movement is performed in a number of ways. In the past, markers attached to anatomical landmarks on the subject were filmed, and then the markers were hand digitized to determine their position in free space. However, with data rates as high as 500-1,000 pictures per second, the process was very time consuming. The excessive time resulted in high analysis costs and excessive delays before final results were obtained.
In recent years the development of video cameras with high frame rates and shuttered input have spurred the development of automated motion analysis systems. With such cameras, visual information is immediately available as an electric signal that can be conveniently stored on video tape and thereafter made available for analysis by computer. In one system, not necessarily in the prior art, infrared light emitting diodes are placed on anatomical sites on a patient. The diodes are turned on in sequence by a host computer and sensed by a camera. However, reflections of the radiation emitted by the diodes off walls, etc., tend to confound the acquisition system. Furthermore, the patient is forced to be cabled to the system, and this inhibits mobility. Some systems use telemetry to turn on the diodes. However, telemetry systems typically are not a reliable means of information transfer.
In another system, also not necessarily in the prior art, illuminated markers are placed on anatomical sites on a patient, and an image preprocessor derives the marker information from a scanned image of the patient. The markers are detected by comparing the amplitude value of each pixel in the image scan lines to a threshold value. When the amplitude of a pixel exceeds the threshold value, the position of the pixel in the scan line is saved so that the marker may be reproduced by a master CPU on a display screen and used in the motion analysis algorithms. However, measurement resolution is often inadequate for clinical gait studies in part because a pixel with an amplitude barely greater than the threshold value is processed the same as pixel values which greatly exceed the threshold value. Furthermore, because the raw data must typically be processed by the master CPU, operation is overly complex, slow, and frequently requires a trained technician in most settings.